Improving the Accuracy of Rapid Antigen Tests for Covid-19 using Data Mining and Blood Test

Abstract

PCR tests are known to give the most accurate results, but are not suitable for mass testing. This article suggests the use of data extraction to diagnose Covid-19. For this purpose, data from rapid antigen tests, external signs of infection and general blood count are processed. The result is that the reliability of antigen tests increases from 50% to over 72%. The future development of the system is to generate a hypothesis about the likelihood of complex application of Covid-19. PCR tests are known to give the most accurate results, but are not suitable for mass testing.